• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.237-252
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• 2017

In recent years, data centers have become the core infrastructure to deal with big data processing. For these big data applications, network transmission has become one of the most important factors affecting the performance. In order to improve network utilization and reduce job completion time, in this paper, by real-time monitoring from the application layer, we propose job-aware priority scheduling. Our approach takes the correlations of flows in the same job into account, and flows in the same job are assigned the same priority. Therefore, we expect that flows in the same job finish their transmissions at about the same time, avoiding lagging flows. To achieve load balancing, two approaches (Flow-based and Spray) using ECMP (Equal-Cost multi-path routing) are presented. We implemented our scheme using NS-2 simulator. In our evaluations, we emulate real network environment by setting background traffic, scheduling delay and link failures. The experimental results show that our approach can enhance the Hadoop job execution efficiency of the shuffle stage, significantly reduce the network transmission time of the highest priority job.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4701-4719
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• 2015

A Mobile Ad hoc Network (MANET) consists of mobile nodes which co-operate to forward each other's packets without the presence of any centralized authority. Due to this lack of centralized monitoring authority, MANETs have become vulnerable to various kinds of routing misbehaviour. Sometimes, nodes exhibit non-cooperating behaviour for conserving their own resources and exploiting others' by relaying their traffic. A node may even drop packets of other nodes in the guise of forwarding them. This paper proposes an efficient Reputation and Collaboration technique through route-request for handling such misbehaving nodes. It lays emphasis not only on direct observation but also considers the opinion of other nodes about misbehaving nodes in the network. Unlike existing schemes which generate separate messages for spreading second-hand information in the network, nodes purvey their opinion through route-request packet. Simulation studies reveal that the proposed scheme significantly improves the network performance by efficiently handling the misbehaving nodes in the network.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.29-39
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• 2006

With the increasing popularity of the wireless network, the vulnerability issue on IEEE 802.1x Wireless Local Area Network (WLAN) are more serious than we expected. Security issues range from mis-configured wireless Access Point(AP) such as session hijacking to Denial of Service(DoS) attack. We propose a new system based on intrusion detection or prevention mechanism to protect the wireless network against these attacks. The proposed system has a security solution on AP that includes an intrusion detection and protection system(IDS/IPS) as an embedded module. In this paper, we suggest integrated wireless IDS/IPS module on AP with wireless traffic monitoring, analysis and packet filtering module against malicious wireless attacks. We also present that the system provides both enhanced security and performance such as on the university wireless campus network.

• Journal of Fisheries and Marine Sciences Education
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• v.19 no.2
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• pp.269-277
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• 2007

We propose the architecture for the bidirectional remote educational system using the APII(Asia-Pacific II) international network. The proposed system was imported function of the VoIP and Web storage with Access Grid System for adopting the various cooperating methods of the remote education, and also implemented the network monitoring functions system using MRTG. Using the proposed methods, we have verified the performance and problems of implemented system through the real-time remote education using bidirectional communication between KOREA and Japan.

• The Transactions of the Korea Information Processing Society
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• v.1 no.4
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• pp.490-501
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• 1994

In this study the problems of cell marking method used in the field of ATM network traffic control are presented. Also an extended cell marking method considering the user level priority is proposed. The conventional traffic monitoring schemes set the CLP bit of a cell to 1 only under the circumstance of the violation of traffic contract. It causes that the number of low level cells increases and the levels of cells are lowered regardless of the user level priority. The three level priority control method combining FCI bit with CLP bit has also been proposed. It divides CLP=0 cells into two levels. Consequently, the proposed method preserves more cells in high level than the conventional one and the real loss of high level cells can be reduced. The performance of the proposed scheme has also been analyzed by the PBS(partial buffer sharing) with two thresholds for the proposed three levels. The result shows that the PBS with two thresholds can give more efficient control than the scheme with no priority, or the PBS with one threshold.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.12
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• pp.1329-1336
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• 2015

Due to the advances in hardware technologies for low-power CMOS cameras, there have been various researches on wireless video sensor network(WVSN) applications including agricultural monitoring and environmental tracking. In such a system, its core technologies include video compression and wireless transmission. Since data of video sensors are bigger than those of other sensors, it is particularly necessary to estimate precisely the traffic after video encoding. In this paper, we present an estimation method for the encoded video traffic in WVSN networks. To estimate traffic characteristics accurately, the proposed method first measures complexities of frames and then applies them to the bit rate estimation adaptively. It is shown by experimental results that the proposed method improves the estimation of bit rate characteristics by more than 12% as compared to the existing method.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.42-48
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• 2011

This paper presents a bridge road surface frost prediction and monitoring system. The node sensing hardware comprises microprocessor, temperature sensors, humidity sensors and Zigbee wireless communication. A software interface is implemented the control center to monitor and acquire the temperature and humidity data of bridge road surface. A bridge road surface frost occurs when the bridge deck temperature drops below the dew point and the freezing point. Measurement data was used for prediction of road surface frost occurrences. The actual alert is performed at least 30 minutes in advance the road surface frost. The road surface frost occurrences data are sent to nearby drivers for traffic accidents prevention purposes.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.5
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• pp.571-580
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• 2012

Epidemiologic studies of air pollution need accurate exposure assessments at unmonitored locations. A land use regression (LUR) model has been used successfully for predicting traffic-related pollutants, although its application has been limited to Europe, North America, and a few Asian region. Therefore, we modeled traffic-related pollutants by LUR then examined whether LUR models could be constructed using a regulatory monitoring network in Metropolitan area in Korea. We used the annual-mean nitrogen dioxide ($NO_2$) in 2010 in the study area. Geographic variables that are considered to predict traffic-related pollutants were classified into four groups: road type, traffic intensity, land use, and elevation. Using geographical variables, we then constructed a model to predict the monitored levels of $NO_2$. The mean concentration of $NO_2$ was 30.71 ppb (standard deviation of 5.95) respectively. The final regression model for the $NO_2$ concentration included five independent variables. The LUR models resulted in $R^2$ of 0.59. The mean concentration of $NO_2$ of elementary schools was 34.04 ppb (standard deviation of 5.22) respectively. The present study showed that even if we used regulatory monitoring air quality data, we could estimate $NO_2$ moderately well. These analyses confirm the validity of land use regression modeling to assign exposures in epidemiological studies, and these models may be useful tools for assessing health effects of long-term exposure to traffic related pollution.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1836-1842
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• 2015

On road networks, the clustering of moving objects is important for traffic monitoring and routes recommendation. The existing schemes find out density route by considering the number of vehicles in a road segment. Since they don’t consider the features of each road segment such as width, length, and directions in a road network, the results are not correct in some real road networks. To overcome such problems, we propose a clustering method for congested routes discovering from the trajectories of moving objects on road networks. The proposed scheme can be divided into three steps. First, it divides each road network into segments with different width, length, and directions. Second, the congested road segments are detected through analyzing the trajectories of moving objects on the road network. The saturation degree of each road segment and the average moving speed of vehicles in a road segment are computed to detect the congested road segments. Finally, we compute the final congested routes by using a clustering scheme. The experimental results showed that the proposed scheme can efficiently discover the congested routes in different directions of the roads.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.1-8
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• 2023

In this paper, we propose a black ice detection platform framework using Convolutional Neural Networks (CNNs). To overcome black ice problem, we introduce a real-time based early warning platform using CNN-based architecture, and furthermore, in order to enhance the accuracy of black ice detection, we apply a multi-scale dilation convolution feature fusion (MsDC-FF) technique. Then, we establish a specialized experimental platform by using a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Experimental results of a real-time black ice detection platform show the better performance of our proposed network model compared to conventional image segmentation models. Our proposed platform have achieved real-time segmentation of road black ice areas by deploying a road black ice area segmentation network on the edge device Jetson Nano devices. This approach in parallel using multi-scale dilated convolutions with different dilation rates had faster segmentation speeds due to its smaller model parameters. The proposed MsCD-FF Net(2) model had the fastest segmentation speed at 5.53 frame per second (FPS). Thereby encouraging safe driving for motorists and providing decision support for road surface management in the road traffic monitoring department.